5 papers
Patronus: Identifying and Mitigating Transferable Backdoors in Pre-trained Language Models
Tianhang Zhao, Haodong Zhao, Wei Du +5
The ``Pre-train, then fine-tune'' paradigm has revolutionized Natural Language Processing (NLP). In this context, transferable backdoors pose a severe threat to the Pre-trained Lan…
Do Latent Tokens Think? A Causal and Adversarial Analysis of Chain-of-Continuous-Thought
Yuyi Zhang, Boyu Tang, Tianjie Ju +2
Latent tokens are gaining attention for enhancing reasoning in large language models (LLMs), yet their internal mechanisms remain unclear. This paper examines the problem from a re…
Judge Before Answer: Can MLLM Discern the False Premise in Question?
Jidong Li, Lingyong Fang, Haodong Zhao +2
Multimodal large language models (MLLMs) have witnessed astonishing advancements in recent years. Despite these successes, MLLMs remain vulnerable to flase premise problems. Howeve…
Probing then Editing Response Personality of Large Language Models
Tianjie Ju, Zhenyu Shao, Bowen Wang +7
Large Language Models (LLMs) have demonstrated promising capabilities to generate responses that simulate consistent personality traits. Despite the major attempts to analyze perso…
Keep the General, Inject the Specific: Structured Dialogue Fine-Tuning for Knowledge Injection without Catastrophic Forgetting
Yijie Hong, Xiaofei Yin, Xinzhong Wang +7
Large Vision Language Models have demonstrated impressive versatile capabilities through extensive multimodal pre-training, but face significant limitations when incorporating spec…